EP 3494512 B1 20230517 - A METHOD FOR LEARNING A VEHICLE BEHAVIOUR OF A MONITORED AUTOMOBILE AND A RESPECTIVE AUTOMOBILE
Title (en)
A METHOD FOR LEARNING A VEHICLE BEHAVIOUR OF A MONITORED AUTOMOBILE AND A RESPECTIVE AUTOMOBILE
Title (de)
VERFAHREN ZUM LERNEN EINES FAHRZEUGVERHALTENS EINES ÜBERWACHTEN AUTOMOBILS SOWIE ZUGEHÖRIGES AUTOMOBIL
Title (fr)
PROCÉDÉ D'APPRENTISSAGE D'UN COMPORTEMENT DE VÉHICULE D'UNE AUTOMOBILE SURVEILLÉE, ET AUTOMOBILE ASSOCIÉE
Publication
Application
Priority
- EP 2016068427 W 20160802
- EP 2017069132 W 20170728
Abstract (en)
[origin: WO2018024623A1] It is described a method for learning a vehicle behaviour of a monitored vehicle (100). The method comprises detecting (10) at least a part of a vehicle illumination (110) of the monitored vehicle (100) and monitoring (20) the detected (10) vehicle illumination (110). And if a light-pattern (111) occurs in the detected (10) vehicle illumination (110), wherein the light-pattern (HI) corresponds to a frequency, intensity and/or colour dependant glowing of the vehicle illumination (110), the light-pattern (111) starting with a flashing up of at least a part of the detected (10) vehicle illumination (110) and ending after a certain time without glowing of the respective part of the detected (10) vehicle illumination (110), the method moreover comprises: monitoring (40) the light-pattern (111); monitoring (60) a vehicle movement (120) of the monitored vehicle (100) during the occurrence of the light-pattern (111); and comparing (50) the monitored (40) light-pattern (111) with at least a known light-pattern (211) from a light-pattern data entry (210) stored in an light-pattern database (200). And if the comparison (50) results into the monitored (40) light-pattern (111) being unknown, the method moreover comprises: storing (80) the light-pattern (111) and the vehicle movement (120) together as a new light-pattern data entry (220) into the light-pattern database ( 200 ).
IPC 8 full level
G08G 1/04 (2006.01); G06F 18/2433 (2023.01); G06V 10/96 (2022.01); G06V 20/58 (2022.01); G08G 1/16 (2006.01)
CPC (source: EP US)
B60Q 1/46 (2013.01 - US); G06F 18/22 (2023.01 - US); G06F 18/2433 (2023.01 - EP); G06V 10/96 (2022.01 - EP US); G06V 20/584 (2022.01 - EP US); G08G 1/0112 (2013.01 - US); G08G 1/0129 (2013.01 - US); G08G 1/0133 (2013.01 - US); G08G 1/04 (2013.01 - EP US); G08G 1/161 (2013.01 - EP); G01P 3/36 (2013.01 - US); G01P 13/00 (2013.01 - US); G01P 15/00 (2013.01 - US); G05D 1/0231 (2024.01 - US); G05D 1/0276 (2024.01 - US); H04W 4/46 (2018.01 - US)
Citation (examination)
FEIXIANG REN ET AL: "General traffic sign recognition by feature matching", IMAGE AND VISION COMPUTING NEW ZEALAND, 2009. IVCNZ '09. 24TH INTERNATIONAL CONFERENCE, IEEE, PISCATAWAY, NJ, USA, 23 November 2009 (2009-11-23), pages 409 - 414, XP031599986, ISBN: 978-1-4244-4697-1
Designated contracting state (EPC)
AL AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HR HU IE IS IT LI LT LU LV MC MK MT NL NO PL PT RO RS SE SI SK SM TR
DOCDB simple family (publication)
WO 2018024623 A1 20180208; CN 109643375 A 20190416; CN 109643375 B 20231031; EP 3494512 A1 20190612; EP 3494512 B1 20230517; JP 2019530054 A 20191017; US 11562574 B2 20230124; US 2019163996 A1 20190530; WO 2018024320 A1 20180208
DOCDB simple family (application)
EP 2017069132 W 20170728; CN 201780053981 A 20170728; EP 17751320 A 20170728; EP 2016068427 W 20160802; JP 2019505485 A 20170728; US 201916264964 A 20190201